code: def test_leave_out_prefix_tuning(self):
      # Note: for prefix tuning, this test is a little weird as the prefix tuning weights are only returned for the first layer with a prefix and not all.
      # It still kind of tests the right thing as we prune layers from the end, which will move the returned layer to the next layer with a prefix.
      model = self.get_model()
      self.run_leave_out_test(
          model, PrefixTuningConfig(flat=True), self.leave_out_layers
      )
  
file_path: adapters/tests/methods/test_prefix_tuning.py
imports: import torch
  from adapters import ADAPTER_MODEL_MAPPING, AutoAdapterModel, PrefixTuningConfig
  from transformers import CLIPConfig
  from transformers.testing_utils import require_torch, torch_device
  from .base import AdapterMethodBaseTestMixin
label_desc: Use image node_id 2 for calling the PrefixTuningTestMixin obj's underlying member method code with example usage: obj.test_leave_out_prefix_tuning() without return types